1.0 - 8.00 - Closeness Arguments - Teradata Vantage

Teradata® Vantage Machine Learning Engine Analytic Function Reference

Product
Teradata Vantage
Release Number
1.0
8.00
Release Date
May 2019
Content Type
Programming Reference
Publication ID
B700-4003-098K
Language
English (United States)
TargetKey
Specify the target key (the names of the edges table columns that identify the target vertex). If you specify targets_table, then the function uses only the vertices in targets_table as targets (which must be a subset of those that this argument specifies).
Directed
[Optional] Specify whether the graph is directed.
Default: 'true'
EdgeWeight
[Optional] Specify the name of the edges table column that contains edge weights. The weights are positive values.
Default behavior: The weight of each edge is 1 (that is, the graph is unweighted).
MaxDistance
[Optional] Specify the maximum distance (an integer) between the source and target vertices. A negative max_distance specifies an infinite distance. If vertices are separated by more than max_distance, the function does not output them.
Default: 10
GroupSize
[Optional] Specify the number of source vertices that run a SNSP algorithm in parallel. If group_size exceeds the number of source vertices in each partition, s, then s is the group size. Running a group of vertices on each vworker, in parallel, uses less memory than running all vertices on each vworker.
Default behavior: The function calculates the optimal group size based on cluster and query characteristics.
SampleRate
[Optional] Specify the sample rate (the percentage of source vertices to sample), a numeric value in the range (0, 1].
Default: 1
Accumulate
[Optional] Specify the names of the vertices table columns to copy to the output table. These columns enable you to identify the different closeness scores in the output table.